Search Results - (( using vector error algorithm ) OR ( parameter estimation path algorithm ))
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Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems
Published 2005“…Estimated parameters from recent measurements ([PMFOO]) are compared with estimated parameters from model generated waveforms as well as theoretical distribution of received signal's angular spread. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
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Web Algorithm search engine based network modelling of Malaria Transmission
Published 2013“…There are observed cases of attempting vector control on a trial and errors basis, with no scientific way of determining the locations of critical vector densities. …”
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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Distance vector-hop range-free location algorithm for wireless sensor network
Published 2015“…Distance Vector-Hop (DV-Hop) algorithm has become the focus of studies for range-free localization algorithms. …”
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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Short term forecasting based on hybrid least squares support vector machines
Published 2018“…In this study, hybrid Least Squares Support Vector Machines (LSSVM) with four meta-heuristic algorithms viz. …”
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Flood Control Distance Vector Hop (FCDV-Hop) localization in wireless sensor networks
Published 2020“…Distance Vector-Hop (DV-Hop) localization is a distributed, hop by hop positioning algorithm. …”
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Two steps hybrid calibration algorithm of support vector regression and K-nearest neighbors
Published 2020“…The hybrid algorithm was evaluated using a dataset of pipeline corrosion measurements collected by a Magnetic Flux Leakage (MFL) sensor (with an error margin of ±20 of the true values), and an Ultrasonic (UT) device (with an error margin of ±4). …”
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A new countermeasure to combat the embedding-based attacks on the goldreich-goldwasser-halevi lattice-based cryptosystem
Published 2024“…In this study, we showed that the error vector �⃗! is not unique. We proposed another error vector �⃗∗ to combat the embedding-based attacks. …”
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A new countermeasure to combat the embedding-based attacks on the Goldreich-Goldwasser-Halevi lattice-based cryptosystem
Published 2024“…Consequently, the simplified CVP can be reduced to a Shortest-Vector Problem (SVP) variant which can be solved by using lattice-reduction algorithms such as the LLL algorithm in a shorter amount of time. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Five evaluation metrics were utilized; mean average percent error (MAPE), accuracy, symmetric mean absolute percent error (SMAPE), root mean square percent error (RMSPE) and fitness value. …”
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Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
Published 2018“…The algorithm works if the quadrotor undergoes a deviation, an admissible trajectory path is generated for the quadrotor rapidly return on the straight-line route. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network
Published 2023“…This artificial intelligent call admission control (CAC) was validated using a dynamic WCDMA mobile network simulator. A few comparative results in downlink have shown that our integrated support vector regression assists genetic algorithm (SVRaGA) is capable of predicting next interval power consumption at Node B with low prediction error and improving the quality of service (QoS) by reducing dropped calls. � 2008 IEICE.…”
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Error Detection of Personalized English Isolated-Word Using Support Vector Machine
Published 2012“…Subsequently, a well-known classification type of artificial intelligent algorithm namely Support Vector Machine (SVM) is used to evaluate those features under two class types of words with proper segregation of correct and erroneous words in two data sets. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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